code: def sparse_mx_to_torch_sparse_tensor(sparse_mx):
      """Convert a scipy sparse matrix to a torch sparse tensor."""
      sparse_mx = sparse_mx.tocoo().astype(np.float32)
      indices = torch.from_numpy(
          np.vstack((sparse_mx.row, sparse_mx.col)).astype(np.int64)
      )
      values = torch.from_numpy(sparse_mx.data)
      shape = torch.Size(sparse_mx.shape)
      return torch.sparse.FloatTensor(indices, values, shape)
  
file_path: PGL/examples/chebnetii/ogb/processing.py
imports: import numpy
  import torch
  import pickle
  import argparse
  from ogb.nodeproppred.dataset_pyg import PygNodePropPredDataset
  import scipy.sparse
  from torch_geometric.utils import to_undirected
  from torch_sparse import SparseTensor
label_desc: Use image node_id 2 for calling a global function with example usage: sparse_mx_to_torch_sparse_tensor(sparse_mx) and returns: torch